The elaboration and empirical evaluation of the De Goede learning potential structural model
CITATION: Van Heerden, S. & Theron, C. 2014. The elaboration and empirical evaluation of the De Goede learning potential structural model. South African Journal of Business Management, 45(3):a128, doi:10.4102/sajbm.v45i3.128.
The original publication is available at https://sajbm.org
As a direct result of having segregated amenities and public services during the Apartheid era where Black individuals were provided with services inferior to those of White individuals, the country is currently challenged by serious and a debilitating skills shortage across most industry sectors, high unemployment and poverty rates, and inequality in terms of income distribution as well as in terms of racial representation in the workforce. These challenges are the consequence of a larger problem that knowledge, skills and abilities are not uniformly distributed across all races. In the past, and still now, White South Africans had greater access to skills development and educational opportunities. It is this fundamental inequality that has to be addressed. It is argued that skills development – specifically affirmative action skills development should form part of the solution. A need therefore exists to identify the individuals who would gain maximum benefit from such affirmative action skills development opportunities and to create the conditions that would optimise learning performance. To achieve this, an understanding is required of the complex nomological network of latent variables that determine learning performance. De Goede (2007) proposed and tested a learning potential structural model based on the work of Taylor (1994). The primary objective of this study was to expand on De Goede’s (2007) learning potential structural model in order to gain a deeper understanding of the complexity underlying learning performance. A subset of the hypothesised expanded learning potential structural model was empirically evaluated. The first analysis of the structural model failed to produce a good fit to the data. The model was subsequently modified by both adding additional paths and by removing insignificant paths. The final revised structural model was found to fit the data well. All paths contained in the final model were empirically corroborated. The practical implications of the learning potential structural model on HR and organisations are discussed. Suggestions for future research are made by indicating how the model can be further elaborated. The limitations of the study are also discussed.